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An Intelligent GIS and Meta-Heuristic Based Emergency Vehicle Routing Framework for Smart Urban Healthcare Systems
Subject area: Science,Engineering and Technology · Area of research: Computer Science
DOI: https://doi.org/10.64388/IREV9I11-1717975
Abstract
Emergency medical response systems play a critical role in reducing mortality during life-threatening situations where rapid transportation and timely intervention are essential. Existing ambulance routing and dispatch systems primarily rely on static distance-based navigation approaches that fail to account for dynamic urban challenges such as traffic congestion, infrastructure damage, signal interference, and unstable network connectivity. Several studies have explored GPS-enabled dispatching, GIS-based traffic systems, swarm intelligence algorithms, and Tele-EMS integration; however, most existing frameworks remain fragmented and lack real-time synchronization with smart-city infrastructure.This paper presents a comprehensive review of current emergency vehicle routing methodologies and identifies major research gaps in dynamic traffic integration, disaster-aware routing, network-aware navigation, and scalable urban routing architectures. Based on these gaps, a novel intelligent routing framework is proposed that combines GIS-based traffic synchronization, meta-heuristic optimization algorithms, predictive congestion analysis, and network-aware path planning. The proposed framework aims to improve ambulance response efficiency, reduce navigation delays, maintain stable Tele-EMS connectivity, and support adaptive routing during urban emergencies and disaster scenarios. The study contributes a structured review of existing approaches, identifies limitations in current systems, and proposes a scalable smart emergency transportation model for future urban healthcare infrastructure.
Keywords
Emergency Vehicle Routing GIS-Based Navigation Smart City Infrastructure Meta-Heuristic Optimization Tele-EMS Ambulance Dispatch Systems Swarm Intelligence
References
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How to cite this paper
@article{1717975,
author = {Judith Kezia Wilson, Dr. Balamurugan S},
title = {An Intelligent GIS and Meta-Heuristic Based Emergency Vehicle Routing Framework for Smart Urban Healthcare Systems},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {11},
pages = {2622-2626},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1717975.pdf},
abstract = {Emergency medical response systems play a critical role in reducing mortality during life-threatening situations where rapid transportation and timely intervention are essential. Existing ambulance routing and dispatch systems primarily rely on static distance-based navigation approaches that fail to account for dynamic urban challenges such as traffic congestion, infrastructure damage, signal interference, and unstable network connectivity. Several studies have explored GPS-enabled dispatching, GIS-based traffic systems, swarm intelligence algorithms, and Tele-EMS integration; however, most existing frameworks remain fragmented and lack real-time synchronization with smart-city infrastructure.This paper presents a comprehensive review of current emergency vehicle routing methodologies and identifies major research gaps in dynamic traffic integration, disaster-aware routing, network-aware navigation, and scalable urban routing architectures. Based on these gaps, a novel intelligent routing framework is proposed that combines GIS-based traffic synchronization, meta-heuristic optimization algorithms, predictive congestion analysis, and network-aware path planning. The proposed framework aims to improve ambulance response efficiency, reduce navigation delays, maintain stable Tele-EMS connectivity, and support adaptive routing during urban emergencies and disaster scenarios. The study contributes a structured review of existing approaches, identifies limitations in current systems, and proposes a scalable smart emergency transportation model for future urban healthcare infrastructure.},
keywords = {Emergency Vehicle Routing GIS-Based Navigation Smart City Infrastructure Meta-Heuristic Optimization Tele-EMS Ambulance Dispatch Systems Swarm Intelligence},
month = {May},
doi = {https://doi.org/10.64388/IREV9I11-1717975}
}